PLZ HELP what is discrete, normal distribution ,central tendency, standard deviation, variance.?

Question

what is discrete, normal distribution ,central tendency, standard deviation, variance.?

my homework is to find the meanings of these words. i have them but i dont know wat they stand for? plz help.

Answer 1

Those terms refers to statistics . For a tutorial check:
http://psych.utoronto.ca/courses/c1/statstoc.htm
http://www.stattrek.com/Lesson1/Sets.aspx
http://www.stats.gla.ac.uk/steps/glossary/alphabet.html

Discrete and continuous variables
* If a variable has a basic unit of measurement that cannot be subdivided, it is a discrete variable. The measurement process for discrete variables involves accurate counting of the number of units per case. E.g. number of people per household is a discrete variable. The basic unit is people, and the fewest you can have is one. The score will always be a whole number because you will never be able to find 2.7 people living in a specific household.
* A variable is continuous if the measurement of it can be subdivided infinitely-at least in a theoretical sense. E.g. time, which can be measured in nanoseconds or even smaller units. In as sense, when we are measure a continuous variable, we are always approximating and rounding off the scores.
* The difference between these two variables relates more to measuring and processing the information than to the appearance of the data.

The distribution of a variable is a description of the relative numbers of times each possible outcome will occur in a number of trials. .

The normal distribution: A frequency histogram of the result obtained from repetitive measurements made of variables, frequently follows a characteristic shape likened to that of an upside down bell - The Normal Distribution.

Mean The arithmetic average of all values.

Dispersion: the amount of variety or heterogeneity in a distribution of scores

Standard deviation is a measure of the spread or dispersion of a set of data, it's a value which describes the spread of the population about the mean and as such is a property of the population.

Variance: The (population) variance of a random variable is a non-negative number which gives an idea of how widely spread the values of the random variable are likely to be; the larger the variance, the more scattered the observations on average.
Stating the variance gives an impression of how closely concentrated round the expected value the distribution is; it is a measure of the 'spread' of a distribution about its average value.

Central tendency is the number that represents the "middle" of a set of numbers. The arithmetic mean is the sum of the observations divided by the number of observations. It is the most common statistic of central tendency, and when someone says simply "the mean" or "the average," this is what they mean.

Hope this help

Answer 2

In statistics a discrete random variable defines a particular type of variable (in contrast to a continuous random variable The normal distribution, also called Gaussian distribution, is an extremely important probability distribution in many fields. It is a family of distributions of the same general form, differing in their location and scale parameters: the mean ("average") and standard deviation ("variability"), respectively. The standard normal distribution is the normal distribution with a mean of zero and a standard deviation of one (the green curves in the plots to the right). It is often called the bell curve because the graph of its probability density resembles a bell. Central tendency Measures of central tendency are measures of the location of the middle or the center of a distribution. The definition of "middle" or "center" is purposely left somewhat vague so that the term "central tendency" can refer to a wide variety of measures. The mean is the most commonly used measure of central tendency. The following measures of central tendency are discussed in this text: Mean Median Mode Trimean Trimmed mean In probability and statistics, the standard deviation of a probability distribution, random variable, or population or multiset of values is defined as the square root of the variance. The standard deviation is measured in the same units as the values of the population. For a population of distances in meters, the standard deviation is also measured in meters, whereas the variance is measured in square meters. The standard deviation is the root mean square (RMS) deviation of the values from their arithmetic mean. For example, in the population (4, 8), the mean is 6 and the standard deviation is 2. This may be written: (4, 8) ≈ 6±2. In this case 100% of the values in the population are within two standard deviations away from the mean. In probability theory and statistics, the variance of a random variable (or equivently a probability distribution) is a measure of its statistical dispersion, indicating how its possible values are spread around the expected value. Where the expected value shows the location of the distribution, the variance indicates the scale of the values. A more understandable measure is the square root of the variance, called the standard deviation. As its name implies it gives in a standard form an indication of the possible deviations from the mean. The variance of a real-valued random variable is its second central moment, and it also happens to be its second cumula

Answer 3

well standard deviation means how much the averages can vary eg a rivers avg depth is 7m and std devin is 5 that means the max depth is 7m + 5 or depth can decrease also ie 7-5
variance measures to which side it varies the most
i think central tendency means averages mode median etc

Answer 4

google statistics...